Backend Software Engineer, TikTok Live Recommendation Infrastructure
Core
Design and build backend systems and model infrastructure for large-scale live-stream recommendation workloads, including training, inference, and data pipelines.
Role type
Senior IC backend software engineer (ML infrastructure)
Builds
Scalable training pipelines, low-latency inference serving, and data pipelines for TikTok Live recommendation systems
Domain
Internet / Recommendation Systems / Distributed Systems
Deliverable
production ML models
Required skills
C++, Go, Java, Python, distributed systems, backend service development, ML infrastructure, model serving, inference optimization, large-scale training systems, data pipelines (Spark, Flink, Kafka, Hadoop)
Preferred skills
recommendation systems, ranking, personalization platforms, deep learning frameworks (TensorFlow, PyTorch), cloud-native environments (Kubernetes), performance optimization for low-latency systems, live streaming, content delivery, real-time systems
Responsibilities
Design and build backend systems supporting large-scale recommendation workloads; Develop robust and efficient model infrastructure including distributed training and low-latency inference; Architect and improve data pipelines for feature engineering; Collaborate with ML engineers to productionize models; Drive performance optimization and cost-efficiency; Ensure system robustness and scalability in high-traffic scenarios